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title: README |
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Multimodal Art Projection (M-A-P) is an opensource research community. |
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The coummnity members are working on Artificial Intelligence-Generated Content (AIGC) topics, including text, audio, and vision modalities. |
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We do large language/music models (LLMs/LMMs) training, data collection, and development of fun applications. |
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Welcome to join us! |
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Organization page: https://m-a-p.ai |
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The development log of our Multimodal Art Projection (m-a-p) model family: |
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- 23/01/2024: we release [**CMMMU**](https://huggingface.co/datasets/m-a-p/CMMMU) for better Chinese LMMs' Evaluation. |
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- 13/01/2024: 🔥 we release a series of **Music Pretrained Transformer (MuPT)** checkpoints, with [**size up to 1.3B and 8192 context length**](https://huggingface.co/m-a-p/MuPT_v0_8192_1.3B). Our models are **LLAMA2**-based, pre-trained on **world's largest 10B tokens symbolic music dataset** ([ABC notation format](https://en.wikipedia.org/wiki/ABC_notation)). We currently support Megatron-LM format and will release huggingface checkpoints soon. |
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- 02/06/2023: officially release the [MERT pre-print paper](https://arxiv.org/abs/2306.00107) and training [codes](https://github.com/yizhilll/MERT). |
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- 17/03/2023: we release two advanced music understanding models, [MERT-v1-95M](https://huggingface.co/m-a-p/MERT-v1-95M) and [MERT-v1-330M](https://huggingface.co/m-a-p/MERT-v1-330M) , trained with new paradigm and dataset. They outperform the previous models and can better generalize to more tasks. |
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- 14/03/2023: we retrained the MERT-v0 model with open-source-only music dataset [MERT-v0-public](https://huggingface.co/m-a-p/MERT-v0-public) |
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- 29/12/2022: a music understanding model [MERT-v0](https://huggingface.co/m-a-p/MERT-v0) trained with **MLM** paradigm, which performs better at downstream tasks. |
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- 29/10/2022: a pre-trained MIR model [music2vec](https://huggingface.co/m-a-p/music2vec-v1) trained with **BYOL** paradigm. |
